Event processing systems are coming into increasingly widespread use in a variety of different enterprises. However, existing event processing systems have a number of significant drawbacks. For example, such systems often require custom-built transformations for each different type of input event information to be processed, and are generally unable to detect, normalize and combine event information from multiple federated information sources. Also, the existing event processing systems are typically very limited in terms of the complexity of events that can be recognized and processed.
A given enterprise may therefore have to combine multiple disparate event processing systems in order to handle complex events. In addition, exception handling in such arrangements often requires extensive human intervention. As a result, the deployment of complex event processing functionality can be unduly expensive and time-consuming for the enterprise.
The above-noted drawbacks are becoming increasingly problematic as virtual infrastructure becomes more widely distributed over larger numbers of physical machines. For example, commercially available virtualization software such as VMware® vSphere™ may be used to build a variety of different types of virtual infrastructure, including private and public cloud computing and storage systems, distributed across hundreds of interconnected physical computers and storage devices. As the complexity of such cloud-based systems increases, the need for accurate and efficient event processing has also grown. Unfortunately, existing event processing systems are not easily able to accommodate this increasing complexity of enterprise infrastructure.
Accordingly, a need exists for an improved approach to the detection and processing of complex events in an information processing system.